edu.stanford.nlp.optimization

Class SMDMinimizer<T extends Function>

java.lang.Object

edu.stanford.nlp.optimization.StochasticMinimizer<T>

edu.stanford.nlp.optimization.SMDMinimizer<T>

All Implemented Interfaces:

HasEvaluators, Minimizer<T>

public class SMDMinimizer<T extends Function>
extends StochasticMinimizer<T>

Stochastic Meta Descent Minimizer based on
Accelerated training of conditional random fields with stochastic gradient methods S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy June 2006 Proceedings of the 23rd international conference on Machine learning ICML '06 Publisher: ACM Press
The basic way to use the minimizer is with a null constructor, then the simple minimize method:

Minimizer smd = new SMDMinimizer();
DiffFunction df = new SomeDiffFunction();
double tol = 1e-4;
double[] initial = getInitialGuess();
int maxIterations = someSafeNumber;
double[] minimum = qnm.minimize(df,tol,initial,maxIterations);
Constructing with a null constructor will use the default values of

batchSize = 15;
initialGain = 0.1;
useAlgorithmicDifferentiation = true;

Since:

1.0

Version:

1.0

Author:

Alex Kleeman

Nested Class Summary

Nested classes/interfaces inherited from class edu.stanford.nlp.optimization.StochasticMinimizer

StochasticMinimizer.PropertySetter<T1>

Field Summary

Fields

Modifier and Type	Field and Description
double	cPosDef
double	lam
double	meta
double	mu
boolean	printMinMax

Fields inherited from class edu.stanford.nlp.optimization.StochasticMinimizer

bSize, file, gain, gen, grad, gradList, infoFile, k, maxTime, memory, newGrad, newX, nf, numBatches, numPasses, outputFrequency, outputIterationsToFile, quiet, v, x

Constructor Summary

Constructors

Constructor and Description
SMDMinimizer()
SMDMinimizer(double initialSMDGain, int batchSize, StochasticCalculateMethods method, int passes)
SMDMinimizer(double initGain, int batchSize, StochasticCalculateMethods method, int passes, boolean outputToFile)

Method Summary

Modifier and Type	Method and Description
protected java.lang.String	getName()
protected void	init(AbstractStochasticCachingDiffFunction func)
static void	main(java.lang.String[] args)
double[]	minimize(Function function, double functionTolerance, double[] initial) Attempts to find an unconstrained minimum of the objective function starting at initial, accurate to within functionTolerance (normally implemented as a multiplier of the range value to give range tolerance).
void	setBatchSize(int batchSize)
void	shutUp()
protected void	takeStep(AbstractStochasticCachingDiffFunction dfunction)
Pair<java.lang.Integer,java.lang.Double>	tune(Function function, double[] initial, long msPerTest)

Methods inherited from class edu.stanford.nlp.optimization.StochasticMinimizer

gainSchedule, minimize, say, sayln, setEvaluators, smooth, tune, tuneBatch, tuneDouble, tuneDouble, tuneGain

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

mu

public double mu

lam

public double lam

cPosDef

public double cPosDef

meta

public double meta

printMinMax

public boolean printMinMax

Constructor Detail

SMDMinimizer

public SMDMinimizer()

SMDMinimizer

public SMDMinimizer(double initialSMDGain,
                    int batchSize,
                    StochasticCalculateMethods method,
                    int passes)

SMDMinimizer

public SMDMinimizer(double initGain,
                    int batchSize,
                    StochasticCalculateMethods method,
                    int passes,
                    boolean outputToFile)

Method Detail

shutUp

public void shutUp()

Overrides:

shutUp in class StochasticMinimizer<T extends Function>

setBatchSize

public void setBatchSize(int batchSize)

minimize

public double[] minimize(Function function,
                         double functionTolerance,
                         double[] initial)

Description copied from interface: Minimizer

Attempts to find an unconstrained minimum of the objective function starting at initial, accurate to within functionTolerance (normally implemented as a multiplier of the range value to give range tolerance).

Specified by:

minimize in interface Minimizer<T extends Function>

Overrides:

minimize in class StochasticMinimizer<T extends Function>

Parameters:

function - The objective function

functionTolerance - A double value

initial - An initial feasible point

Returns:

Unconstrained minimum of function

init

protected void init(AbstractStochasticCachingDiffFunction func)

Overrides:

init in class StochasticMinimizer<T extends Function>

tune

public Pair<java.lang.Integer,java.lang.Double> tune(Function function,
                                                     double[] initial,
                                                     long msPerTest)

Specified by:

tune in class StochasticMinimizer<T extends Function>

takeStep

protected void takeStep(AbstractStochasticCachingDiffFunction dfunction)

Specified by:

takeStep in class StochasticMinimizer<T extends Function>

getName

protected java.lang.String getName()

Specified by:

getName in class StochasticMinimizer<T extends Function>

main

public static void main(java.lang.String[] args)